Data Engineer (Business Intelligence)

As a Data Engineer, you will be a cornerstone of the global Systems and Software organization, supporting Business Intelligence through the Microsoft suite of analytics and data platforms. You will focus on the technical implementation of data gathering, integration, and model design, utilizing tools like SQL, Azure, Microsoft Fabric, and Power BI to build robust architectures for strategic and self-service business intelligence.

Key Responsibilities

Data Architecture & Pipeline Management

• Infrastructure Development: Design, build, and maintain robust data architectures, data warehouses, and large-scale processing systems to power analytics initiatives.
• ETL/ELT Oversight: Implement and manage complex Extract, Transform, and Load (ETL) or Extract, Load, and Transform (ELT) processes for seamless data ingestion from diverse sources.
• Optimization: Continuously monitor and optimize data pipelines and infrastructure to ensure maximum performance and efficiency.

Data Governance & Quality

• Standards & Compliance: Ensure data quality, security, and compliance by implementing industry best practices in data governance.
• Engineering Excellence: Adhere to internal standards for coding, project tracking, and documentation to ensure scalable and maintainable solutions.

Stakeholder Collaboration & BI Support

• Strategic Partnerships: Work closely with data analysts to understand their requirements and provide clean, accessible data for their reporting needs.
• Cross-Functional Integration: Partner with product owners, data architects, and software engineers to ensure data infrastructure is reliable and aligns with business goals.
• BI Delivery: Utilize BI services to support both strategic enterprise models and self-service reporting for business users.

Requirements

Education & Experience

• Education: Bachelor's degree in Computer Science, Information Technology, or a related field.
• Professional Tenure: Minimum of 5 years of relevant experience in Data Engineering, Data Warehousing, or Database Management.
• Cloud Expertise: Hands-on experience with at least one major cloud platform (e.g., Azure, AWS, or GCP).

Technical Skills

• Data Warehousing: Solid understanding of warehousing concepts and experience with solutions such as Snowflake, BigQuery, or Redshift.
• Connectivity: Extensive experience connecting to various data structures, including RDBMS, Data Lakes, SQL Databases, and Cloud Infrastructure.
• Tooling: Proficiency in SQL, Azure, Microsoft Fabric, and Power BI.

Preferred Qualifications

• Advanced SQL: Working experience in SQL services is highly valued.
• Agile Methodologies: Knowledge of Agile or Scrum delivery methods is a significant plus.